Job
In this role, you will develop ML-based tools for analyzing X-ray and neutron scattering data, collaborate in an international team, and present scientific results at conferences and in publications.
Job technologies
Your role in the team
- The research group of Prof. Dr. Dr. h.c. Frank Schreiber at the University of Tübingen works on the physics of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering experiments.
- We are currently looking for a PhD student to join our team and help us make exciting new advances in applications of machine learning (ML) strategies for analyzing X-ray and neutron scattering data.
- You will be working in an international research group at the Institute of Applied Physics together with experienced scientists.
- You will contribute to the top scientific experiments, will obtain practical experience, improve your soft skills (presentation, communication, language, etc), learn the strategies of data organization and analysis.
- Development of ML-based tools to analyse data from different surface sensitive scattering techniques (X-ray Reflectivity (XRR), Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS) and others).
- Contribution to the scattering data analysis and support of data/metadata formats developed in the group.
- Integration of the developed software into the computational environments and data handling routines.
- Presentation of the scientific results on conferences and in publications.
Our expectations of you
Education
- Master's degree in physics or chemistry, computer science or equivalent.
Qualifications
- Candidates should have good communication skills and motivation to familiarize themselves with new subject areas.
- The role requires both independent work and effective collaboration, particularly during measurement campaigns at synchrotron and neutron facilities.
- Participation in teaching activities (e.g., supervising practical courses or tutorials) may also be possible.
- Interest in Physics and Machine Learning.
- Good written and spoken English.
- Ability to work both independently and in a team.
- Programming skills (Python) and acquaintance with modern machine learning frameworks (PyTorch/JAX) are strong advantages.
Experience
- Experience with programming languages such as Python is advantageous.
What we offer
- The positions offered provide access to challenging and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium.
- The group offers well-equipped laboratories, a highly collaborative international environment and membership of the Cluster of Excellence "Machine Learning: New Perspectives for Science", which is funded by the DFG and is located at the University of Tübingen.
- Students in the group receive excellent training and supervision and the opportunity to conduct research at large-scale international facilities, such as synchrotron and neutron sources.
Topics you will work on
Job locations
About your employer
The Eberhard Karls University of Tübingen is a university located in the German state of Baden-Württemberg. It was founded in 1477 at the behest of Count Eberhard im Bart and is thus one of the oldest universities in Europe. It is also named after the first Duke of Württemberg, Karl Eugen.
- 250+ Employees
- Established Company
- Hybrid, Onsite
- Education System
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